Designing Inclusive Artificial Intelligence Systems
AI has the power to transform lives, but only if it's designed with everyone in mind.
Ensuring that AI systems are accessible to people with disabilities is essential for promoting inclusivity and equal access. It is essential to approach the development and deployment of AI with careful consideration of ethical implications, transparency, and inclusivity, ensuring that its benefits are accessible and distributed equitably. Here are some practical guidelines for making AI systems accessible to people with disabilities.
Apply Inclusive Design Principles
Incorporate inclusive design principles from the outset of AI system development. Consider the diverse needs of people with disabilities throughout the design process, ensuring accessibility features are built-in rather than retrofitted. Apply the Web Content Accessibility Guidelines to the interface design, focusing on ensuring that all AI interfaces are perceivable, operable, understandable and robust enough to accommodate everyone’s needs.
Insist on Representative Unbiased Data
For disabled communities, one of the biggest concerns about AI is potential for biased output and outcomes because of a unrepresentative data set and existing human biases. Ensure the training data used for AI algorithms is diverse, representative, and inclusive. Include data that reflects the experiences and characteristics of people with disabilities. This helps AI systems to learn and make accurate predictions that cater to the needs of individuals with disabilities. And if data sets are biased, call it out. Biases will continue if we don’t correct the data.
Accommodate Flexible Input and Output Options
Design NLP models that are inclusive and accommodate diverse communication styles. Train the models to understand and respond to various speech patterns, accents, and speech impairments. Provide alternative input methods, such as text-based input or gesture recognition, for individuals who cannot use speech-based interfaces. Consider using audio-based cues or haptic feedback to convey information about visual content.
Use Plain Language
Not everyone is tech savvy, or fluent in English. Ensure that all prompts, content and suggestions are simple, clear and unambiguous, avoiding jargon and technical terms. It is also important to ensure that the prompts and output are appropriate and helpful, using respectful and people first language. All content needs to be relevant and contextual.
Enable Personalisation and Customisation
Enable AI systems to personalise experiences based on individual needs. Allow users to customise interface settings, such as font size, colour contrast, and interaction preferences. Provide options for alternative input methods and navigation controls to accommodate various motor disabilities.
Include People with Disabilities
Engage with individuals with disabilities to gain insights into their specific requirements and preferences in the design and testing and evaluation of AI systems. Their feedback is invaluable in identifying accessibility barriers and areas for improvement. Conduct usability testing, user interviews, and engage accessibility experts to gain insights into the user experience of individuals with disabilities.
Collaborate with Accessibility Experts
Collaborate with accessibility experts, consultants, and auditors to ensure the accessibility of AI systems. Their expertise can provide guidance, conduct audits, and offer recommendations for improving accessibility. Engage them in accessibility reviews, code audits, and user testing to ensure comprehensive accessibility considerations.
Check Accuracy of Recommendations
AI systems are not 100% infallible. Don’t believe everything that AI systems create. Ensure AI models for visual recognition accurately describe visual content to accommodate individuals with visual impairments. Provide alternative text descriptions for images, videos, and other visual elements. If accurate descriptions are not possible the system needs further work.
Continuously Monitor and Improve
Regularly monitor and evaluate the accessibility of AI systems over time. Gather feedback from users with disabilities, accessibility experts, and the wider community to identify areas for improvement. Continuously update and refine AI models and algorithms to enhance accessibility and address emerging accessibility challenges.
Increase Transparency and Awareness
Most people do not know or fully understand the extent of AI applications. More transparency is required about what is ‘real’ and what has been AI generated. We need to enhance the transparency of AI systems by providing explanations of how decisions and content is made. For example, for people with cognitive disabilities, provide simplified explanations or visual aids to help comprehension. This allows users to understand and trust the outputs and decisions made by the AI system.
By following these guidelines and collaborating with accessibility experts, AI systems can be designed and developed to be inclusive and accessible, catering to the needs of people with disabilities. Our next post in the series tackles the Benefits, and Risks, of Artificial Intelligence. If you’d like to know more about making your AI systems inclusive, reach out. We are always happy to help.